numpy.indices(dimensions, dtype=<class 'int'>)
[source]
Return an array representing the indices of a grid.
Compute an array where the subarrays contain index values 0,1,… varying only along the corresponding axis.
Parameters: |
dimensions : sequence of ints The shape of the grid. dtype : dtype, optional Data type of the result. |
---|---|
Returns: |
grid : ndarray The array of grid indices, |
The output shape is obtained by prepending the number of dimensions in front of the tuple of dimensions, i.e. if dimensions
is a tuple (r0, ..., rN-1)
of length N
, the output shape is (N,r0,...,rN-1)
.
The subarrays grid[k]
contains the N-D array of indices along the k-th
axis. Explicitly:
grid[k,i0,i1,...,iN-1] = ik
>>> grid = np.indices((2, 3)) >>> grid.shape (2, 2, 3) >>> grid[0] # row indices array([[0, 0, 0], [1, 1, 1]]) >>> grid[1] # column indices array([[0, 1, 2], [0, 1, 2]])
The indices can be used as an index into an array.
>>> x = np.arange(20).reshape(5, 4) >>> row, col = np.indices((2, 3)) >>> x[row, col] array([[0, 1, 2], [4, 5, 6]])
Note that it would be more straightforward in the above example to extract the required elements directly with x[:2, :3]
.
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.indices.html